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    Modelling asynchronous distributed e-Learning environment

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    Date
    2009
    Author
    Kariuki, Paul N
    Type
    Thesis
    Language
    en
    Metadata
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    Abstract
    The world today has some very advanced lCT services and high quality life indicators. The existing online e-Iearning environments have been designed with this in mind, and are therefore reliant on reliable means of communication for their access. However, access to Internet which facilitates access to these online e-Iearning environments is not universal, and poses a significant cost to the user. The lack of access to online educational resources whether for economical or logistics reasons excludes otherwise eligible students from the course. This is a significant issue in rural and lower socioeconomic neighborhoods. On the other hand, occasional loss of connectivity, bandwidth provider problems or the need to take down parts of the network for maintenance still renders asynchronous communication dependant e-Iearning system inaccessible at times. This calls for new methods and technology to supplement traditional online based training and instruction and provide continuous learning even when offline. This research project present an Asynchronous Distributed e-Iearning Environment model that overcomes the challenges faced in the usage and implementation of synchronous communication dependant e-Iearning platforms. The learning environment proposed in this research overcomes the infrastructural challenges of access to online learning environment by providing an alternative mechanism that allows learning to continue even with minimal or unreliable communication infrastructure, thereby overcoming the infrastructural access barrier posed by the convectional e-Iearning environment. The system is modeled in conformity with the existing e-Iearning systems that are driven by network connectivity, having most of the features that are characteristic of todav's e-Iearning platform.
    URI
    http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/26320
    Citation
    Masters of Medicine (Applied Computer Science)
    Publisher
    University of Nairobi
     
    School of Computing and Informatics
     
    Collections
    • Faculty of Science & Technology (FST) [4213]

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